Reinforcement-Learning

This post explains two terms you will run into often in multi-agent reinforcement learning: CTDE and MAPPO. It also covers a practical question that does not get written down much — which of these papers you can actually reproduce, and whether you need a GPU. I will keep the wording simple and stay close to what the source papers say. The setting: more than one agent In standard reinforcement learning, a single agent takes actions in an environment and learns from rewards. Multi-agent reinforcement learning (MARL) is the same idea, but with several agents acting at the same time. Examples: several robots that must cooperate, or several units in a game that share a goal. ...